Fetching the paper…
Reading the bibliography…
Fuzzing has played an important role in improving software development and testing over the course of several decades.
Optimizing seed inputs in fuzzing with machine learning
Liang Cheng, Yang Zhang, Yi Zhang, Chen Wu, Zhangtan Li, Yu Fu, and Haisheng Li. 2019 · 1902
Earlier work this paper cites.
A Report on Random Testing. In Proceedings of the 5th International Conference on Software Engineering (ICSE ’81) . IEEE Press, Piscataway, NJ, USA, 179–183
Joe W. Duran and Simeon Ntafos. 1981 · 1981
Earlier work this paper cites.
An Evaluation of Random Testing
Joe W. Duran and Simeon C. Ntafos. 1984 · 1984
Earlier work this paper cites.
An Empirical Study of the Reliability of UNIX Utilities
Barton P. Miller, Louis Fredriksen, and Bryan So. 1990 · 1990
Earlier work this paper cites.
Application of artificial neural networks in process fault diagnosis
Timo Sorsa and Heikki N. Koivo. 1993 · 1993
Earlier work this paper cites.
Reinforcement Learning: A Survey
Leslie Pack Kaelbling, Michael L. Littman, and Andrew W. Moore. 1996 · 1996
Earlier work this paper cites.
Violating Assumptions with Fuzzing
Peter Oehlert. 2005 · 2005
Earlier work this paper cites.
Revolutionizing the Field of Grey-box Attack Surface Testing with Evolutionary Fuzzing
Jared D. DeMott, Richard J. Enbody, and William F. Punch. 2007 · 2007
Earlier work this paper cites.
Automated Vulnerability Analysis: Leveraging Control Flow for Evolutionary Input Crafting. In Twenty-Third Annual Computer Security Applications Conference (ACSAC 2007) . 477–486
Sherri Sparks, Shawn Embleton, Ryan K Cunningham, and Cliff Changchun Zou. 2007 · 2007
Earlier work this paper cites.
Vulnerability Analysis for X86 Executables Using Genetic Algorithm and Fuzzing. In 2008 Third International Conference on Convergence and Hybrid Information Technology , Vol. 2. 491–497
Guang-Hong Liu, Gang Wu, Zheng Tao, Jian-Mei Shuai, and Zhuo-Chun Tang. 2008 · 2008
Earlier work this paper cites.
Fuzzing for Software Security Testing and Quality Assurance
Ari Takanen, Jared Demott, and Charlie Miller. 2008 · 2008
Earlier work this paper cites.
An Autonomic Testing Framework for IPv6 Configuration Protocols. In Mechanisms for Autonomous Management of Networks and Services , Burkhard Stiller and Filip De Turck (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 65–76
Sheila Becker, Humberto Abdelnur, Radu State, and Thomas Engel. 2010 · 2010
Earlier work this paper cites.
Tackling the Path Explosion Problem in Symbolic Execution-Driven Test Generation for Programs. In Proceedings of the 2010 19th IEEE Asian Test Symposium (ATS ’10) . IEEE Computer Society, Washington, DC, USA, 59–64
Saparya Krishnamoorthy, Michael S. Hsiao, and Loganathan Lingappan. 2010 · 2010
Earlier work this paper cites.
Making Software Dumber
Tavis Ormandy. 2010 · 2010
Earlier work this paper cites.
Reinforced Adaptive Large Neighborhood Search. Doctoral Program at the Interational Conference on Principles and Practice of Constraint Programming, 55–60
Jean-Baptiste Mairy, Yves Deville, and Pascal Van Hentenryck. 2011 · 2011
Earlier work this paper cites.
Efficient Loop Navigation for Symbolic Execution
Jan Obdrzálek and Marek Trtík. 2011 · 2011
Earlier work this paper cites.
Constraint Programming meets Machine Learning and Data Mining. In Dagstuhl Seminar
Luc De Raedt, Siegfried Nijssen, Barry O’Sullivan, and Pascal Van Hentenryck. 2011 · 2011
Earlier work this paper cites.
ReBucket: A method for clustering duplicate crash reports based on call stack similarity
Yingnong Dang, Rongxin wu, Hongyu Zhang, Dongmei Zhang, and Peter Nobel. 2012 · 2012
Earlier work this paper cites.
SAGE: Whitebox Fuzzing for Security Testing
Patrice Godefroid, Michael Y. Levin, and David Molnar. 2012 · 2012
Earlier work this paper cites.
ImageNet Classification with Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
Earlier work this paper cites.
Fault diagnosis on production systems with support vector machine and decision trees algorithms
M. Demetgul. 2013 · 2013
Earlier work this paper cites.
Fuzz in the Dark: Genetic Algorithm for Black-Box Fuzzing. In Black Hat 2013 . Black Hat, Sao Paulo, Brazil
Fabien Duchene. 2013 · 2013
Earlier work this paper cites.
Generating Sequences With Recurrent Neural Networks
Alex Graves. 2013 · 2013
Cited alongside, same era.
Playing Atari with Deep Reinforcement Learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller. 2013 · 2013
Cited alongside, same era.
Scheduling Black-box Mutational Fuzzing. In Proceedings of the 2013 ACM SIGSAC Conference on Computer Communications Security (CCS ’13) . ACM, New York, NY, USA, 511–522
Maverick Woo, Sang Kil Cha, Samantha Gottlieb, and David Brumley. 2013 · 2013
Cited alongside, same era.
Board-Level Functional Fault Diagnosis Using Multikernel Support Vector Machines and Incremental Learning
F. Ye, Z. Zhang, K. Chakrabarty, and X. Gu. 2014 · 2013
Cited alongside, same era.
Neural Machine Translation by Jointly Learning to Align and Translate
Not all bytes are equal: Neural byte sieve for fuzzing
William Blum, Mohit Rajpal, and Rishabh Singh. 2017 · 2017
Later among the works it cites.
Directed Greybox Fuzzing. In Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (CCS ’17) . ACM, New York, NY, USA, 2329–2344
Marcel Böhme, Van-Thuan Pham, Manh-Dung Nguyen, and Abhik Roychoudhury. 2017 · 2017
Later among the works it cites.
Graph Neural Networks and Boolean Satisfiability
Benedikt Bünz and Matthew Lamm. 2017 · 2017
Later among the works it cites.
Gaslight: A comprehensive fuzzing architecture for memory forensics frameworks. In 2017 17th Annual DFRWS (Volume 22) . Digital Investigation, USA, 86–93
Andrew Case, Arghya Kusum Das, Seung-Jong Park, J. (Ram) Ramanujam, and Golden G.Richard III. 2017 · 2017
Later among the works it cites.
A Review of Fuzzing Tools and Methods
James Fell. 2017 · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
afl-fuzz: crash exploration mode
lcamtuf. 2014 · 2014
Cited alongside, same era.
Optimizing Seed Selection for Fuzzing. In Proceedings of the 23rd USENIX Conference on Security Symposium (SEC’14) . USENIX Association, Berkeley, CA, USA, 861–875
Alexandre Rebert, Sang Kil Cha, Thanassis Avgerinos, Jonathan Foote, David Warren, Gustavo Grieco, and David Brumley. 2014 · 2014
Cited alongside, same era.
Sequence to Sequence Learning with Neural Networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Cited alongside, same era.
Sulley: Fuzzing Framework
Pedram Amini and Aaron Portnoy. 2015 · 2015
Cited alongside, same era.
How Heartbleed could’ve been found
Hanno Böck. 2015 · 2015
Cited alongside, same era.
A Critical Review of Recurrent Neural Networks for Sequence Learning
Zachary C. Lipton, John Berkowitz, and Charles Elkan. 2015 · 2015
Cited alongside, same era.
Hack the Hacker - Fuzzing Mimikatz on Windows with WinAFL & Heatmaps (0DAY)
René Freingruber. 2017 · 2017
Later among the works it cites.
Learn & Fuzz: Machine Learning for Input Fuzzing. In Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017) . IEEE Press, Piscataway, NJ, USA, 50–59
Patrice Godefroid, Hila Peleg, and Rishabh Singh. 2017 · 2017
Later among the works it cites.
Root cause analysis of software bugs using machine learning techniques. In 2017 7th International Conference on Cloud Computing, Data Science Engineering - Confluence . 105–111
H. Lal and G. Pahwa. 2017 · 2017
Later among the works it cites.
libFuzzer - a library for coverage-guided fuzz testing
LLVM. 2017 · 2017
Later among the works it cites.
VUzzer: Application-aware evolutionary fuzzing . Proceedings of the Network and Distributed System Security Symposium (NDSS)
Sanjay Rawat, Vivek Jain, Ashish Kumar, Lucian Cojocar, Cristiano Giuffrida, and Herbert Bos (Eds.). 2017 · 2017
Later among the works it cites.
Survey on Models and Techniques for Root-Cause Analysis
Marc Solé, Victor Muntés-Mulero, Annie Ibrahim Rana, and Giovani Estrada. 2017 · 2017
Later among the works it cites.
Valgrind tool
Valgrind. 2017 · 2017
Later among the works it cites.
Improve SAT-solving with Machine Learning
Haoze Wu. 2017 · 2017
Later among the works it cites.
ExploitMeter: Combining Fuzzing with Machine Learning for Automated Evaluation of Software Exploitability. In 2017 IEEE Symposium on Privacy-Aware Computing (PAC) . 164–175
Guanhua Yan, Junchen Lu, Zhan Shu, and Yunus Kucuk. 2017 · 2017
Later among the works it cites.
American Fuzzy Lop
Michal Zalewski. 2017 · 2017
Later among the works it cites.
Angora: Efficient Fuzzing by Principled Search. In 2018 IEEE Symposium on Security and Privacy (SP) . 711–725
Peng Chen and Hao Chen. 2018 · 2018
Later among the works it cites.
Automatic Heap Layout Manipulation for Exploitation. In 27th USENIX Security Symposium (USENIX Security 18) . USENIX Association, Baltimore, MD
Sean Heelan, Tom Melham, and Daniel Kroening. 2018 · 2018
Later among the works it cites.
George Klees, Andrew Ruef, Benji Cooper, Shiyi Wei, and Michael Hicks. 2018 · 2018
Later among the works it cites.
Learning a SAT Solver from Single-Bit Supervision
Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, and David L. Dill. 2018 · 2018
Later among the works it cites.
NEUZZ: Efficient Fuzzing with Neural Program Smoothing
Dongdong She, Kexin Pei, Dave Epstein, Junfeng Yang, Baishakhi Ray, and Suman Jana. 2018 · 2018
Later among the works it cites.
Neuro-Symbolic Execution: Augmenting Symbolic Execution with Neural Constraints. In NDSS Symposium 2019
Shen Shiqi, Shweta Shinde, Soundarya Ramesh, Abhik Roychoudhury, and Prateek Saxena. 2019 · 2019
Closest in time.
NeuFuzz: Efficient Fuzzing With Deep Neural Network
Yunchao Wang, Zehui Wu, Qiang Wei, and Qingxian Wang. 2019 · 2019
Closest in time.